<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta keyword="刘焕勇 知识图谱 事理图谱 金融 情报 语言资源 常识知识库 常识库 事理 演化 推理 简历 中科院 软件所 中国科学院 数据地平线">
    <title>刘焕勇-个人主页</title>
    <link rel="stylesheet" type="text/css" href="Semantic-ui/semantic.min.css">
    <script src="Semantic-ui/semantic.min.js"></script>
</head>
<body>
<div class="ui celled grid">
  <div class="two wide column">
     </div>
  <div class="twelve wide column">
  <div class="ui items">
  <div class="item">
    <div class="image">
        <img src="./images/liuhuanyong.png">
    </div>
    <div class="content">
      <div class="description">
         <p><font size="3"><a href="https://liuhuanyong.github.io">刘焕勇</a>，语言学及应用语言学硕士，目前就职于<a href="www.iscas.ac.cn">中国科学院软件研究所</a>，兼任<a href="https://datahorizon.cn">数据地平线科技</a>算法总监、<a href="https://www.aegis-info.com/">南京擎盾科技</a>技术顾问，专注金融、情报两大领域，从事事件抽取、事件演化、情感分析、<a href="https://www.jiqizhixin.com/articles/2018-12-29-23">事理（知识）图谱</a>、常识推理、语言资源构建与应用等研发工作。目前发表相关论文两篇、发明专利（含实审中)两项、主持研发自然语言处理技术开放平台<a href="https://nlp.datahorizon.cn">数地工场</a>、大规模实时事理知识学习系统<a href="xueji.datahorizon.cn">学迹</a>、全行业因果链查询与溯源项目<a href="https://eg.datahorizon.cn">寻链系统</a>，并在智能金融、智能情报落地中负责实施了多个项目。致力于面向中文处理的基础知识库建设与理论技术开源共享，目前累计对外开放<a href="https://liuhuanyong.github.io">自然语言处理实践项目</a>六十余个，其中知识图谱与事理图谱类项目十六项。在openkg开放知识图谱联盟中开放<a href="http://www.openkg.cn/organization/datahorizon">工业应用知识库</a>七类，主笔<a href="https://mp.weixin.qq.com/s/5ZW5JnZob2u0IrWBoCoxjw">数地工场</a>技术类系列文章二十余篇。</font></p>
         <p><font size="3">邮箱:lhy_in_blcu@126.com</font></p>
         <p><font size="3">地址:北京市海淀区中关村南四街4号</font></p> 
         <p><font size="3">github:<a href="https://github.com/liuhuanyong">https://github.com/liuhuanyong</a>，<a href="http://githubrank.com">githubrank</a></font></p> 
        </div>
    </div>
  </div>    
      
    <h3 class="ui horizontal divider header"><i class="project icon"></i> 代表论文 </h3>
<table class="ui three column table">
<tbody>
    <tr>
      <td><a href="http://sigkg.cn/ccks2020/?page_id=53">2020：刘焕勇等.面向开放文本的逻辑推理知识抽取与事件影响推理探索,Accpeted in 2020 China Conference on Knowledge Graph and Semantic Computing(CCKS 2020)</a></td>
    </tr>
    <tr>
      <td><a href="http://www.soopat.com/Patent/201811354870">2019：刘焕勇.一种因果事件图谱构建方法、系统、装置及存储介质,专利.109726293A</a></td> 
    </tr> 
    <tr>
      <td><a href="http://www.soopat.com/Patent/201810864029">2018：刘焕勇.一种行业文本情感获取方法、装置及存储介质,专利.109284499A</a></td>
    </tr>  
    <tr>
      <td><a href="http://202.112.206.6:808/docinfo.action?id1=ae44be0c43508e2faf61fcc9ee50d4b8&id2=Y0VXDDVRn%252BA%253D">2017：刘焕勇.语言政策领域知识图谱构建初探[D].北京语言大学,2017</a></td>
    </tr>
    <tr>
      <td><a href="http://www.cnki.com.cn/Article/CJFDTotal-TSSF201604011.htm">2016：刘焕勇.也说“就”[J],唐山师范学院学报,2016年04期</a></td>
    </tr>
     </tbody>
</table>    
    
    <h3 class="ui horizontal divider header"><i class="project icon"></i> 负责项目 </h3>
<table class="ui three column table">
  <thead>
    <tr>
      <th>年份</th>
      <th>项目名称</th>
      <th>项目技术点</th>
    </tr>
  </thead>
<tbody> 
 <tr>
      <td>2020</td>
      <td><a href="https://soso.datahorizon.cn">数地搜搜事件实例搜索与分析平台</a></td>
      <td>实时系统，事理应用，事件追踪，事件检索</td>
    </tr>      
 <tr>
      <td>2020</td>
      <td><a href="https://xueji.datahorizon.cn">学迹:大规模实时事理学习与搜索系统</a></td>
      <td>实证学习，信息检索、问答搜索，知识推理</td>
    </tr> 
  <tr>
      <td>2020</td>
      <td><a href="https://nlp.datahorizon.cn">数地工场:面向事件与数据的开放语义平台</a></td>
      <td>信息抽取、舆情分析、语义计算、信息采集等API</td>
   </tr>
   <tr>
      <td>2019</td>
      <td><a href="https://eg.datahorizon.cn">全行业事理图谱查询系统</a></td>
      <td>前因后果模式的搜索展示</td>
    </tr>  
   <tr>
       <td>2019</td>
      <td><a href="http://www.openkg.cn/organization/datahorizon?q=&sort=views_recent+desc"> 事理为核心的开放知识图谱资源</a></td>
      <td>知识库数据、知识图谱、开放共享</td>
   </tr> 
   <tr>
       <td>2018</td>
      <td><a href="http://yqsj.datahorizon.cn/index">融合情感与事件的金融期货监控与预测系统</a></td>
      <td>情感分析、事件预测、舆情监控</td>
   </tr>  
   <tr>
       <td>2018</td>
      <td><a href="http:101.201.102.233/kg_editor"> Datagravition金融知识图谱处理系统</a></td>
      <td>图谱编辑、图谱构建、图谱可视化、事件驱动</td>
   </tr> 
   <tr>
       <td>2017</td>
      <td><a href="https://github.com/liuhuanyong/LanguageKnowledgeGraph">语言政策领域知识图谱系统</a></td>
      <td>语言政策本体、语言政策分析、图谱分析与搜索</td>
   </tr> 
    </tbody>
</table>     
      
    <h3 class="ui horizontal divider header"><i class="project icon"></i> 开源项目（62项） </h3>
     
  <h4 class="ui horizontal divider header"><i class="tag icon"></i>知识图谱与事理图谱（16项）</h4>
  <table class="ui three column table">
  <thead>
    <tr>
      <th>项目名称</th>
      <th>中文名称</th>
      <th>项目技术点</th>
    </tr>
  </thead>
  <tbody>
   <tr>
      <td><a href="https://github.com/liuhuanyong/CognitiveInference">CognitiveInference</a></td>
      <td>认知常识知识库与常识推理</td>
      <td>常识知识库、常识推理、推理评估测试</td>
    </tr> 
   <tr>
      <td><a href="https://github.com/liuhuanyong/EventKGNELL">EventKGNELL</a></td>
      <td>学迹事理实时知识库终身学习</td>
      <td>事件知识库，实时学习，事件概念，事理逻辑，语言资源</td>
    </tr> 
      <tr>
      <td><a href="https://github.com/liuhuanyong/ZhidaoChatbot">ZhidaoChatbot</a></td>
      <td>基于问答社区的逻辑知识问答</td>
      <td>问答社区，逻辑问答</td>
    </tr>  
    <tr>
      <td><a href="https://github.com/liuhuanyong/EventPredictBasedOnEG">EventPredictBasedOnEG</a></td>
      <td>基于事理图谱的未来事件预测</td>
      <td>事理图谱，事件预测</td>
    </tr> 
       <tr>
      <td><a href="https://github.com/liuhuanyong/ComplexEventExtraction">ComplexEventExtraction</a></td>
      <td>复合事件图谱</td>
      <td>复合事件，条件事件、反转事件抽取</td>
    </tr>  
    <tr>
      <td><a href="https://github.com/liuhuanyong/CausalityEventExtraction">CausalityEventExtraction</a></td>
      <td>因果事件图谱</td>
      <td>因果图谱，因果事件抽取</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/SequentialEventExtration">SequentialEventExtration</a></td>
      <td>顺承事件图谱</td>
      <td>动宾短语提取，事件图谱</td>
    </tr>  
   <tr>
      <td><a href="https://github.com/liuhuanyong/AbstractKnowledgeGraph">AbstractKnowledgeGraph</a></td>
      <td>抽象知识图谱</td>
      <td>抽象知识图谱，抽象实体，抽象状态，抽象动作</td>
    </tr>  
      <tr>
      <td><a href="https://github.com/liuhuanyong/GoodsKG">GoodsKG</a></td>
      <td>电商商品概念与销售知识图谱</td>
      <td>商品概念，商品类知识</td>
    </tr>  
    <tr>
      <td><a href="https://github.com/liuhuanyong/HyponymyExtraction">HyponymyExtraction</a></td>
      <td>上下位关系图谱</td>
      <td>模式匹配，上下位概念表示</td>
    </tr> 
    <tr>
      <td><a href="https://github.com/liuhuanyong/QAonMilitaryKG">QAonMilitaryKG</a></td>
      <td>军事知识图谱与问答项目</td>
      <td>知识图谱,军事,基于模板问答方式</td>
    </tr>     
    <tr>
      <td><a href="https://github.com/liuhuanyong/TravelKnowledgeGraph">TravelKnowledgeGraph</a></td>
      <td>出行知识图谱</td>
      <td>路径规划,推荐,知识模型</td>
    </tr>     
    <tr>
      <td><a href="https://github.com/liuhuanyong/PersonRelationKnowledgeGraph">PersonRelationKnowledgeGraph</a></td>
      <td>中文人物关系图谱</td>
      <td>bootstrapping, 远程监督, 训练数据回标, 关系抽取</td>
    </tr>       
    <tr>
      <td><a href="https://github.com/liuhuanyong/QASystemOnMedicalKG">QASystemOnKG</a></td>
      <td>医疗知识图谱与自动问答</td>
      <td>知识图谱构建及自动问答</td>
    </tr>  
    <tr>
      <td><a href="https://github.com/liuhuanyong/LanguageKnowledgeGraph">LanguageKnowledgeGraph</a></td>
      <td>语言政策知识图谱</td>
      <td>Neo4j,Echarts,D3js</td>
    </tr>
     <tr>
      <td><a href="https://github.com/liuhuanyong/TextGrapher">TextGrapher</a></td>
      <td>文本结构化图谱表示</td>
      <td>EventExtraction，知识表示</td>
    </tr>   
  </tbody>
  </table>    
    
 <h4 class="ui horizontal divider header"><i class="tag icon"></i>语言资源与学习心得（11项）</h4>
      
<table class="ui three column table">
  <thead>
    <tr>
      <th>项目名称</th>
      <th>中文名称</th>
      <th>项目技术点</th>
    </tr>
  </thead>
<tbody>
         <tr>
      <td><a href="https://github.com/liuhuanyong/KnowledgeGraphSlides">KnowledgeGraphSlides</a></td>
      <td>知识图谱CCKS会议报告合集(2013-2018)</td>
      <td>知识图谱, 学习资源</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/CCKS2018Summary">CCKS2018Summary</a></td>
      <td>CCKS2018会议总结</td>
      <td>知识图谱,个人心得</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/CCL2018Summary">CCL2018Summary</a></td>
      <td>CCL2018参会总结</td>
      <td>自然语言处理,心得</td>
    </tr>
    </tbody>
      <tr>
      <td><a href="https://github.com/liuhuanyong/ChineseSemanticKB">ChineseSemanticKB</a></td>
      <td>中文处理的12类、百万规模的语义常用词典</td>
      <td>中文处理的12类、百万规模的语义常用词典，支持句子扩展、转写、事件抽象与泛化</td>
    </tr>
  <tr>
      <td><a href="https://github.com/liuhuanyong/MiningZhiDaoQACorpus">MiningZhiDaoQACorpus</a></td>
      <td>知道类问答社区数据集</td>
      <td>语言资源库，语料库，580万问题，983万问答对</td>
    </tr>
    <tr>
      <td><a href=" https://github.com/liuhuanyong/">CausalCollocation</a></td>
      <td>频繁因果词对库</td>
      <td>语言资源库，因果对</td>
    </tr>  
  <tr>
      <td><a href="https://github.com/liuhuanyong/ChineseNLPCorpus">ChineseNLPCorpus</a></td>
      <td>中文自然语言处理处理用语言资源</td>
      <td>语言资源库，语义库，常用词典, 语言资源观, 语料库</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/SentimentWordExpansion">SentimentWordExpansion</a></td>
      <td>情感词扩展</td>
      <td>SOPMI</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/BaikeInfoExtraction">BaikeInfoExtraction</a></td>
      <td>百科信息抽取</td>
      <td>Urllib,xpath</td>
    </tr>
    <tr>

      <td><a href="https://github.com/liuhuanyong/SougouWordCollector">SougouWordCollector</a></td>
      <td>搜狗词库自动构建</td>
      <td>Urllib,Scrapy</td>
    </tr>
    <tr>

      <td><a href="https://github.com/liuhuanyong/BaikeKnowledgeSchema">BaikeKnowledgeSchema</a></td>
      <td>百科知识体系构建</td>
      <td>Urllib,xpath,递归，知识库本体概念</td>
    </tr>

    </tbody>
</table>


    <h4 class="ui horizontal divider header"><i class="tag icon"></i> 自然语言处理基本组件（6项） </h4>
<table class="ui three column table">
  <thead>
    <tr>
      <th>项目名称</th>
      <th>中文名称</th>
      <th>项目技术点</th>
    </tr>
  </thead>
<tbody>
   <tr>
      <td><a href="https://github.com/liuhuanyong/WordSegment">WordSegment</a></td>
      <td>分词</td>
      <td>HMM, MAXCUT,Ngram</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/HuanNLP">HuanNLP</a></td>
      <td>自然语言处理组件</td>
      <td>HMM, maxent, CRF</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/Pinyin2Chinese">Pinyin2Chinese</a></td>
      <td>拼音转文字</td>
      <td>Trie树，HMM, bigram</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/QueryCorrection">QueryCorrection</a></td>
      <td>查询纠错</td>
      <td>edit-distance</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/ChineseCixing">ChineseCixing</a></td>
      <td>中文词形查询</td>
      <td>字形，音形</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/ChineseAntiword">ChineseAntiword</a></td>
      <td>中文反义词查询</td>
      <td>反义词</td>
    </tr>
    </tbody>
</table>


    <h4 class="ui horizontal divider header"><i class="tag icon"></i> 信息抽取（5项） </h4>
<table class="ui three column table">
  <thead>
    <tr>
      <th>项目名称</th>
      <th>中文名称</th>
      <th>项目技术点</th>
    </tr>
  </thead>
<tbody>
     <tr>
      <td><a href="https://github.com/liuhuanyong/WordMultiSenseDisambiguation">WordMultiSenseDisambiguation</a></td>
      <td>中文多义词词义消歧</td>
      <td>百科知识库,词义语义表示,词义语义相似度计算</td>
    </tr>   
    <tr>
      <td><a href="https://github.com/liuhuanyong/TextFeatureExtraction">TextFeatureExtraction</a></td>
      <td>文本特征提取</td>
      <td>IG，CHI ，DF，MI</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/WordCollocation">WordCollocation</a></td>
      <td>搭配抽取</td>
      <td>MI</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/KeyInfoExtraction">KeyInfoExtraction</a></td>
      <td>关键信息提取</td>
      <td>TFIDF，TextRank</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/EventTriplesExtraction">EventTriplesExtraction</a></td>
      <td>事件三元组提取</td>
      <td>dependency parser</td>
    </tr>    
   
  </tbody>
  </table>
    
</table>
    <h4 class="ui horizontal divider header"><i class="tag icon"></i> 文本挖掘与社会计算（17项） </h4>
  <table class="ui three column table">
  <thead>
    <tr>
      <th>项目名称</th>
      <th>中文名称</th>
      <th>项目技术点</th>
    </tr>
  </thead>
    <tr>
      <td><a href="https://github.com/liuhuanyong/IdealWordCloudKit">IdealWordCloudKit</a></td>
      <td>自定义形状词云项目</td>
      <td>wordcloud, tfidf, 可视化</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/WeiboIndexSpyder">WeiboIndexSpyder</a></td>
      <td>微博指数采集</td>
      <td>selenium,xpath</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/BaiduIndexSpyder">BaiduIndexSpyder</a></td>
      <td>百度指数采集</td>
      <td>xpath,selenium</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/AliIndexSpyder">AliIndexSpyder</a></td>
      <td>阿里指数采集</td>
      <td>selenium,xpath</td>
    </tr>
        <tr>
      <td><a href="https://github.com/liuhuanyong/DocSentimentAnalysis">DocSentimentAnalysis</a></td>
      <td>基于句法依存的情感分析</td>
      <td>Template, Dependencyparser</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/LearningBasedSentiment">LearningBasedSentiment</a></td>
      <td>基于深度学习的情感分析</td>
      <td>CNN,RNN,ML</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/HyponymyExtraction">MusicLyricChatbot</a></td>
      <td>歌词对对碰</td>
      <td>es搜索,歌词知识库</td>
    </tr>  
    <tr>
      <td><a href="https://github.com/liuhuanyong/ImportantEventExtractor">ImportantEventExtractor</a></td>
      <td>文本重要性计算</td>
      <td>textrank</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/ZhuguanDetection">ZhuguanDetection</a></td>
      <td>文本主观性计算</td>
      <td>subjective knowledge base</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/SentenceSimilarity">SentenceSimilarity</a></td>
      <td>句子相似度计算</td>
      <td>distance, hash, haiming ,eidtdistance</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/TopicCluster">TopicCluster</a></td>
      <td>文本话题聚类</td>
      <td>LDA，Kmeans</td>
    </tr>
      <tr>
      <td><a href="https://github.com/liuhuanyong/EventMonitor">EventMonitor</a></td>
      <td>特定事件追踪</td>
      <td>新闻采集，事件监测架构，scrapy</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/PoemMining">PoemMining</a></td>
      <td>中国古代诗词挖掘</td>
      <td>语料库构建，文本挖掘</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/LawCrimeMining">LawCrimeMining</a></td>
      <td>司法文本挖掘</td>
      <td>语料库构建，文本挖掘</td>
    </tr>   
    <tr>
      <td><a href="https://github.com/liuhuanyong/CrimeKgAssitant">CrimeKgAssitant</a></td>
      <td>法律罪行智能助手</td>
      <td>知识图谱, 智能预判, 自动问答</td>
    </tr> 
    <tr>
      <td><a href="https://github.com/liuhuanyong/ChineseHumorSentiment">ChineseHumorSentiment</a></td>
      <td>中文幽默情绪计算</td>
      <td>语料库构建，幽默分类与情绪计算</td>
    </tr>  
    <tr>
      <td><a href="https://github.com/liuhuanyong/LanguagePlatform">LanguagePlatform</a></td>
      <td>集成自然语言处理技术的语言平台</td>
      <td>Neo4j,Echarts,Django</td>
    </tr> 
  </tbody>
</table>      
      
    <h4 class="ui horizontal divider header"><i class="tag icon"></i> 深度学习与语义表示（7项） </h4>
  <table class="ui three column table">
  <thead>
    <tr>
      <th>项目名称</th>
      <th>中文名称</th>
      <th>项目技术点</th>
    </tr>
  </thead>
<tbody>
    <tr>
      <td><a href="https://github.com/liuhuanyong/ChineseTextualInference">ChineseTextualInference</a></td>
      <td>中文文本蕴含/推理</td>
      <td>Textual entailment, keras, 文本分类</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/SiameseSentenceSimilarity">SiameseSentenceSimilarity</a></td>
      <td>siamese相似问句匹配</td>
      <td>siamese lstm network, keras, 文本分类</td>
    </tr>        
    <tr>
      <td><a href="https://github.com/liuhuanyong/MedicalNamedEntityRecognition">MedicalNamedEntityRecognition</a></td>
      <td>中文电子病例命名实体识别</td>
      <td>keras, bi-lstm-crf</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/ChineseEmbedding">ChineseEmbedding</a></td>
      <td>中文向量大全(字符向量、词向量、拼音向量、依存向量、词性向量)</td>
      <td>SKIP-GRAM，Co-Matrix</td>
    </tr>
    <tr>
      <td><a href="https://github.com/liuhuanyong/Word2Vector">Word2Vector</a></td>
      <td>词向量表示</td>
      <td>CBOW, SKIP-GRAM，Co-Matrix</td>
    </tr>
   <tr>
      <td><a href="https://github.com/liuhuanyong/Word2Vector">Sentence2Vector</a></td>
      <td>句子向量表示</td>
      <td>CBOW</td>
    </tr>
      <td><a href="https://github.com/liuhuanyong/Seq2SeqTranslation">Seq2SeqTranslation</a></td>
      <td>端到端的翻译模型</td>
      <td>keras, lstm</td>
    </tr>


</tbody>
</table>
  </div> 
  </div>
  <div class="two wide column"></div>
</div>
</body>
</html>
